Pod Resource Calculator
Calculate optimal CPU and memory requests/limits for a Kubernetes pod and the total cluster resources needed across replicas.
Inputs
CPU request per pod, in millicores (1000m = 1 vCPU).
Memory request per pod, in MiB.
Number of pod replicas in the deployment.
Multiplier applied to requests to derive limits (e.g. 2× means limits are double requests).
Total Cluster CPU Request
0.75cores
Total Cluster Memory Request
0.75GiB
Per-Pod CPU Limit
500millicores
Per-Pod Memory Limit
512MiB
Total Cluster CPU Limit
1.50cores
Total Cluster Memory Limit
1.50GiB
Step by step
CPU limit: request × ratio
250m × 2
= 500m
Memory limit: request × ratio
256MiB × 2
= 512MiB
Total CPU request across replicas
250m × 3
= 750m (0.75 cores)
Total memory request across replicas
256MiB × 3
= 768MiB (0.75 GiB)
How it works
Kubernetes schedules pods based on their resource requests, and enforces limits at runtime to prevent a single pod from starving its node. This calculator scales a single pod's CPU and memory request up to the full replica count to show total cluster capacity needed, and applies a limit-to-request ratio to compute the corresponding limits. A ratio of 1 means requests equal limits (Guaranteed QoS); higher ratios allow bursting but increase overcommit risk.
Formulas
Per-pod limit
limit = request × ratio
- R
- Per-pod resource request (CPU or memory)
- \rho
- Limit-to-request ratio
- L
- Per-pod resource limit
Total cluster request
totalRequest = request × replicas
- R
- Per-pod resource request
- N
- Number of replicas
- T
- Total cluster resource request
Frequently Asked Questions
What's the difference between requests and limits?
Requests are what the scheduler reserves for a pod when placing it on a node. Limits are the hard ceiling the kernel enforces — CPU is throttled and memory beyond the limit triggers an OOMKill.
What ratio should I use between requests and limits?
A ratio of 1 (Guaranteed QoS) is safest for predictable latency-sensitive workloads. Ratios of 1.5–3 are common for bursty workloads where you want headroom without over-reserving cluster capacity.
How does replica count affect cluster capacity planning?
Total cluster resources needed scale linearly with replica count. This is what you should compare against your node pool's allocatable capacity when planning autoscaling.
Should I set memory limits equal to requests?
Often yes — unlike CPU, memory can't be reclaimed gracefully, so many teams set memory limits equal to requests to avoid unpredictable OOMKills while still allowing CPU to burst.